Lecture 1: Course Overview and Review of Institutions and Markets

The goals of this class


  1. Understand important financial institutions and markets
  2. Provide a toolkit for creating portfolios of financial assets
  3. Use asset pricing models to understand the trade-off between risk and return
  4. Apply these models to:
    1. identify investment opportunities
    2. evaluate portfolio performance

Who am I?


  • Former research economist at the Federal Reserve Bank of New York (2015-2018)
  • PhD in economics at Harvard from 2009-2015
  • Research associate at the FRBNY (2007-2009)
  • Main research focus:
    1. Consumer finance – bankruptcy, mortgages, housing
    2. Applied statistics – machine learning and other methods
  • Email:
    • Please reach out if you have any concerns or questions re: policy that are not laid out in the syllabus.
  • Website: http://paulgp.github.io

Timeline for our course

Part 1: Institutional details + setting the stage

What we’ll learn:

  • Who are the buyers and issuers of financial instruments?
  • Define assets + securities classes
  • How are financial assets traded?
  • How have these financial assets performed historically?
    • Strong focus on statistical properties and data

Questions to consider:

  • Why do people + institutions trade assets?
  • Why do investments make money?
  • What is the goal of investments?

Timeline for our course

Part 2: Portfolio tools

What we’ll learn

  • How do we interpret observed returns?
    • Build to a model of returns
  • Three ingredients necessary for our models:
    1. Defining risk appetite/aversion
    2. Understanding mean‐variance trade-off
    3. Allocating between risky and safe investments
  • Use models to construct a portfolio of risky investments
    • Capital Asset Pricing Model
    • Arbitrage Pricing Theory / Factor Models

Questions to consider:

  • What is the goal of an investment portfolio?
  • What is risk? How do I quantify it (vs. return)?
  • What simplifications am I willing to assume?

Timeline for our course

Part 3: Critical evaluation of the tools

What we’ll learn

  • How consistent is CAPM with the data?
  • How consistent is the data with APT?
    • Markets are efficient? Or is it behavioral?
  • How should we use the models when there are market anomalies?
    • Active portfolio management
    • Treynor-Black / Black-Litterman
    • Robust Portfolio Management

Questions to consider:

  • Are my portfolio decisions intuitive?
  • What am I missing?

Timeline for our course

Part 4: Evaluate and attribute portfolio returns

What we’ll learn

  • CAPM / APT describe returns from a passive strategy (no skill required)
  • How should we evaluate active managers?
    • Portfolio evaluation techniques answers:

      “Did you beat your benchmark?”

    • Performance attribution answers the question,

      “How did you beat your benchmark?”

Timeline for our course

Part 5: Applications and alternative forms of investing

What are other investment settings?

  • Private equity and hedge funds
  • International investing
  • Fixed income (bonds, futures, forwards)

Key focus:

  • What changes when you shift markets?

Class requirements

  • Straight from the syllabus!
  • Two problem sets as homework:
    • Due February 14, February 28 and March 8
    • To be done individually
  • One case write-ups:
    • Yale University Investments Office (Due in class April 18)
    • To be done in groups 3-5
  • One midterm and one final:
    • March 7 “in class”
    • May 9 “in class”

TA: Lingxiao Xu

Understand the marketplace

Know thy enemy and know yourself; in a hundred battles, you will never be defeated. When you are ignorant of the enemy but know yourself, your chances of winning or losing are equal. If ignorant both of your enemy and of yourself, you are sure to be defeated in every battle.

— Sun Tzu
  1. Who are the participants in the equity market?
    • Overall estimated level AuM (globally) as of 2019: 100+ trillion dollars (or more than global GDP).
    • What institutions hold most assets under management (AUM)?
  2. What incentives do they have?

Institutions

Global assets under management

Institutions

U.S. Institutional Holdings

Institutions

Mutual Funds

  • Also known as open-end funds
    • Investors pool and benefit from sharing information
      collection and back‐office costs
  • Fund issues new shares when investors buy in and redeems shares when investors cash out
  • Priced at Net Asset Value (NAV):


\[ \frac{\text{Market Value of Assets} - \text{Liabilities}}{\text{Shares Outstanding}} \]

Institutions

Mutual Funds Fees

  • Fee Structure: Four types
    1. Operating expenses (recurring)
    2. 12 b‐1 charge (recurring)
    3. Front‐end load (one time)
    4. Back‐end load (one time)
  • Fees must be disclosed in the prospectus
  • Share classes with different fee combinations

Institutions

Example of fees for various classes of mutual funds

  • Compare the A, B and C shares
  • What are the trade-offs between initial and deferred loads?
  • Level of annual fees and expenses

Mutual Funds - fees and incentives

  • People don’t avoid high-fee index funds (Choi et al. 2010)

  • Experimenters overfocused on returns since fund inception

Mutual Funds - fees and incentives

Fund flow response distorts risk-taking incentives (Chevalier and Ellison (1997))

Mutual Funds - costs over time

Mutual fund expense ratios have fallen over time, driven by several factors

  1. Scale economies - assets under management have grown
  2. Competition - investors pick funds with lower expense ratios
  3. Increased presence of employer-sponsored retirement plans

Source: Investment Company Institute

Do mutual fund managers earn their fees?

  • How could we answer this?
  • One idea: how do mutual funds do compared to an index?
  • Performance of actively managed funds below the return on:
    • the Wilshire index in 23 of the 39 years from 1971 to 2009
    • the S&P index in 30 of the 47 years from 1970 to 2017

Matt Levine Reading

  • “Active investment funds should be illegal for fiduciaries.” Do you agree or disagree?

Institutions

Mutual Funds - do fund managers earn their fees?

  • Are all mutual fund managers like Andy Dwyer, or just the average?
  • Malkiel (1995) evaluates 239 mutual funds with at least ten-year records
    • Compare each fund’s performance to holding the S&P 500

Institutions

Is there a “hot hand” for mutual fund managers?

  • Evidence for persistent performance is weak, but suggestive
  • Malkiel (1995) tracks funds based on above/below median performance:

Institutions

Mutual Funds – Persistence in performance?

  • Bollen and Busse (2004) find tiny persistence at the quarterly level

Institutions

Mutual Funds – luck or skill?

Fama French “Luck vs Skill in Mutual Fund Returns” 2010

  • Value weighted portfolio of active funds earns the market return, minus fees
  • Distribution of “alpha” looks more consistent with luck than skill

Net Returns

Institutions

Mutual Funds – luck or skill?

Fama French “Luck vs Skill in Mutual Fund Returns” 2010

  • Value weighted portfolio of active funds earns the market return, minus fees
  • Distribution of “alpha” looks more consistent with luck than skill

Gross Returns

Institutions

Closed-End Funds

  • Unlike mutual funds (open-end), no change in shares outstanding
  • Old investors cash out by selling to new investors
  • Managers unburdened with managing flows
  • Traded continuously on exchanges
  • Priced at premium or discount to NAV
    • No easy arbitrage to close price gaps
  • Hedge funds may ride discounts
    • Alternatively, may attempt to “open” funds

Institutions

What else? Other buyers/Other perspectives

  • Pension funds
  • Endowment Funds
  • Alternative Asset Managers
    • to be discussed in the context of cases and guest lectures
  • Next up…market structure

Market Structure

What kinds of markets are there?

  1. Specialist Markets
  2. Over-the-counter (OTC) markets
  3. Electronic Communication Markets

Market Structure

What types of orders are there?

  • Market order – Buy or sell order to be executed immediately at prevailing bid/ask price
  • Limit order – Buy or sell order with a pre‐specified limit for the price
  • Stop order
    • Buy or sell order at the market price if specified threshold is crossed

Limit orders make up a limit order book

Limit orders make up a limit order book

Market Structure

Types of Markets: Specialist Exchanges

  • Example of a specialist exchange: NYSE
  • Trading traditionally occurred through a combination of an auction (the order book) and a market maker (the specialist)
  • Orders sent to exchange may be cleared electronically or sent to specialist
    • Only one specialist for each stock
    • Specialist may act as broker or as a dealer

Market Structure

Roles of specialists in specialist exchanges

  • Broker
    • Matches buy and sell orders
    • Income generated by commissions
  • Dealer
    • Specialists maintain their own bid and ask quotes and fill orders with own account if market spread too high
    • Historically, participated in about 25% of all transactions
    • Maintained price continuity

Market Structure

Types of Markets: OTC Markets

  • Trades negotiated dealer‐to‐dealer
  • Nasdaq (National Association of Securities Dealers Automated Quotation system)
    • Originally, a price quotation system
    • Large orders may still be negotiated through brokers and dealers
    • Today, NASDAQ provides electronic trading (less OTC)

Market Structure

Types of Markets: Electronic Communication Networks

  • Private computer networks that directly link buyers with sellers for automated order execution
  • To attract liquidity, networks may pay rebates to liquidity providers (market makers)
  • Electronic clearing facilitates high frequency trading

Market Structure

Electronic Communication Networks and high-frequency trading

  • Risks of high speed algorithmic trading include market disruption
  • Flash Crash (2010)
    • On May 6, 2010, US indices fell by more than 5% in a matter of minutes, before rebounding almost as quickly
  • Knight Capital (2012)
    • Flawed deployment of new trading program bankrupts major market maker
    • Lost 440 million dollars from one programming mistake

Market Structure

Electronic Communication Networks and flash crashes

SEC findings suggest the decline was triggered by a large automated sell order for S&P futures by a mutual fund

  • Existing low volume due to high market uncertainty
  • Sell order (75K contracts) was an automated algorithm that directed to sell 9% of prior minute’s trading volume
  • HFTs responded to high volume of trades, but could not find fundamental buyers (SEC describes a game of “hot‐ potato”)
  • High volume led to acceleration in sell order speed, which drove higher volatility and volume

Market Structure

Short-selling

  • In our optimal portfolio, we’ll have the option to “short”–sell stocks that we don’t own
  • Why would we?
    1. Stock may be overpriced (negative alpha)
    2. Stock may be appropriately priced, but we want to hedge out risk from a long position in a similar security (pairs trading)
  • So what is it?

Market Structure

Short-selling Mechanics

Suppose we have one dollar and believe stock A will underperform stock B.

  • Buy $1 of asset B
  • Borrow $1 worth of stock A ( \(1 \big/ P_A\) shares) and promptly sell the stock
    • Now, you owe the owner of A his shares back and will have to repurchase them in the market at tomorrow’s price
    • Proceeds from the sale serve as collateral to stock lender (e.g. $1)
    • Reg T requires 50% additional collateral (above and beyond proceeds) be kept in account (shares of B will suffice)


\[\text{Final Payoff} = 1 + (r_B ‐ r_A) + \ldots+ \underbrace{\text{short rebate}}_{\text{to be defined}}\]

Market Structure

Short-selling Mechanics

  • Assume that \(P_{A} = 100\), and you want to short the stock. What will your return be if the stock drops to \(P_{A} = 25\)?

  • First, calculate your initial position:

    1. You will borrow a share of stock A and sell it immediately. You now have $100 dollars, but owe 1 share of Stock A.
    2. You addditionally post the required 50% collateral (e.g. $50 of a treasury bill)
Assets Liabilities
Cash 100 Short position 100
T-Bill Collateral 50 Equity 50
  • Now imagine the stock drops to \(P_{A}\) = 25 and you close your position:
    1. You buy the stock at $25, and return it to the original owner
    2. The collateral and cash are returned to you, net of your purchase
  • As a result, you have 75 dollars profit. Your return is \(r_{\text{short}} = \frac{75}{100} = 0.75\)
  • Note that the maximum upside is a return of 100%. Why? Because the initial sale at 100$ creates a liability of $100 dollars – at best, this liability goes to zero, netting 100 dollars in profit and a return of 100%.
    • Note that the downside is unlimited.

Market Structure

Short-selling Mechanics

  • Now assume we do this in pairs. There are two stocks, \(A\) and \(B\), each worth 100 dollars.We buy stock \(B\) and short stock \(A\). What will your return be if next period, \(P_{A} = 90\) and \(P_{B} = 105\)?

  • First, calculate your initial position:

    1. You will borrow a share of stock A and sell it immediately. You now have $100 dollars, but owe 1 share of Stock A.
    2. You addditionally post the required 50% collateral (you can post stock \(B\) shares)
Assets Liabilities
Cash 100 Short position 100
Stock B Collateral 50 Equity 100
Stock B 50
  • Now imagine the stocks change to \(P_{A} = 90\) and \(P_{B} = 105\) and you close your position:
    1. You buy the stock at $90, and return it to the original owner
    2. The collateral and cash are returned to you, net of your purchase
    3. You sell Stock B at $105
  • As a result, you have 10 dollars profit from stock A and 5 dollars profit from stock B.
    • Your returns are \(r_{\text{short}} = -r_{A} = 0.1\) and \(r_{\text{long}} = r_{B}\) = 0.05
    • Our total profit is 15 dollars. Our net return is ((100 - 90) + (105 - 100))/100 =0.15.

Market Structure

What is the short rebate?

  • Short rebate is the interest I earn on my dollar of collateral sitting with the stock lender

\[ \text{Short Rebate} = r_{f} - \text{Security lending Fee} \]

  • Securities lending fees vary greatly and reflect how easy the shares are to borrow (often less than 20 bps)
  • In obvious shorting situations, short rebate will go negative (shares “hot or trading “special”) or can’t be found

The peculiar case of GameStop and r/WallStreetBets

Before moving into our example, a quick poll.

  1. Were you aware of Gamestop’s unusual stock market activity in 2021?

  2. Did you buy either Gamestop or AMC or any related “stonks”?

The peculiar case of GameStop and r/WallStreetBets

  • GameStop is a videogame retail company with poor outlook pre-pandemic, and little strategy for the pandemic

    • potential for a “turnaround” with new board members, etc. but unlikely

  • Shorting this stock is a natural strategy

  • However, coordinated stock purchasing (a short squeeze) can make this untenable

    • Why? Short covering creates a feedback loop

Market Structure

Alternative ways to short stocks: synthetic shorts

Consider the following replicating strategy:

  • Buy a put and sell a call at the current strike price
    • Have the option to sell stock at current price (put option)
    • Give someone else the option to buy the stock at today’s price (call option)
  • What happens if real stock goes down 10x? up 10x?
  • However, options traded on less than half of publicly traded firms
  • Moreover, options market behaves badly for “hot shares”
    • Put-call parity is violated by large amounts of short interest